Most HPC systems are clusters of shared memory nodes. Such SMP nodes can be small multi-core CPUs up to large many-core CPUs. Parallel programming may combine the distributed memory parallelization on the node interconnect (e.g., with MPI) with the shared memory parallelization inside of each node (e.g., with OpenMP or MPI-3.0 shared memory). This course analyses the strengths and weaknesses of several parallel programming models on clusters of SMP nodes. Multi-socket-multi-core systems in highly parallel environments are given special consideration. MPI-3.0 has introduced a new shared memory programming interface, which can be combined with inter-node MPI communication. It can be used for direct neighbour accesses similar to OpenMP or for direct halo copies, and enables new hybrid programming models. These models are compared with various hybrid MPI+OpenMP approaches and pure MPI. Numerous case studies and micro-benchmarks demonstrate the performance-related aspects of hybrid programming.
Tools for hybrid programming such as thread/process placement support and performance analysis are presented in a „how-to“ section. This course provides scientific training in Computational Science, and in addition, the scientific exchange of the participants among themselves.
Similar „MPI+X“ tutorials about hybrid programming have been successfully presented by the lecturers Dr. Rolf Rabenseifner (HLRS, member of the steering committee of the MPI-3 Forum) and Dr. Georg Hager (RRZE, winner of the „Informatics Europe Curriculum Best Practices Award: Parallelism and Concurrency“) during various supercomputing conferences in the past.
Teachers: Dr. Georg Hager (RRZE/HPC Uni. Erlangen), Dr. Rolf Rabenseifner (HLRS)
Course: Jan 18, 2018, 10:00-17:00
Registration deadline: Jan 07, 2018
More information about the course and the registration form can be found online on the LRZ and PATC pages: https://www.lrz.de/services/compute/courses/2018-01-18_hhyp1w17/ and http://events.prace-ri.eu/e/LRZ-2018-HHYP1W17